A Versatile Hardware Solution for Generating Power Law Noise With Tunable Long-Term Dependency
Power law noise (PLN) has promising applications in healthcare and artificial intelligence (AI). In this paper, we propose a hardware solution for generating PLN with tunable long-term dependency, by combining the magnetic tunnel junction (MTJ) based two-state Markov chain (MC) generation and modulation method. PLNs with specific parameter α can be obtained by merging multiple two-state MCs. The merged PLN, with α ranging from 0.2 to 1.8 and adjustable long-term dependency as represented by the autocorrelation function (ACF), is demonstrated by varying the voltage conditions applied to the MTJs. This method provides a versatile hardware solution for constructing stochastic signal in semiconductor IC chips.
Authors
- Zheng Chai (ORCID: https://orcid.org/0000-0003-3446-7138)
- J. F. Zhang (ORCID: https://orcid.org/0000-0003-4987-6428)
- Xue Zhou (ORCID: https://orcid.org/0000-0002-2218-0618)
- Xihui Yuan
- Xin Yue (ORCID: https://orcid.org/0000-0002-7625-2701)
- Weidong Zhang (ORCID: https://orcid.org/0000-0003-4600-7382)
- Fangyi Zhao (ORCID: https://orcid.org/0000-0001-8856-7527)
- Tai Min (ORCID: https://orcid.org/0000-0003-4682-4091)
- Yongjie Luo (ORCID: https://orcid.org/0000-0002-2463-2577)
- Jiajia Jian
Institutions
- Liverpool John Moores University (GB)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- IEEE Electron Device Letters
- Published
- 2025-06-06
- DOI
- https://doi.org/10.1109/led.2025.3577161
- Primary Topic
- Power Quality and Harmonics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China